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, computer science, fluid mechanics, or a related area that is considered relevant for the research topic of the project, or have completed courses with a minimum of 240 credits, at least 60 of which must be in
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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communication abilities. A solid background in cell biology, neurobiology, tissue models, or in vitro experimental systems is considered a strong asset for this position. Experience with one or more of the
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in core computer science. Alternatively, you have gained essentially corresponding knowledge in another way. In addition, CUGS requires: a solid knowledge of English, both in spoken and written form as
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in oral and written English. It is considered advantageous if you have solid programming skills in Python, have good knowledge of LaTeX and version control systems (git), and are comfortable working
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corresponding knowledge. You are expected to work in a research laboratory focusing on grief, with emphasis on neural and psychological mechanisms. Experience with experimental work, particularly behavioral tasks
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that you are able to communicate fluently in oral and written English. It is considered advantageous if you have solid programming skills in Python, have good knowledge of LaTeX and version control systems
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graduated at Master’s level in machine learning, statistics, computer science, fluid mechanics, or a related area that is considered relevant for the research topic of the project, or have completed courses
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, network science, and decentralized machine learning. Welcome to read more about us at: https://liu.se/en/organisation/liu/isy/ks . For more information about working at ISY, please visit: https://liu.se/en
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material, and produces high-quality documents. Furthermore, you have a solid understanding of numerical data and can solve numerical tasks quickly and easily. Experience in route optimization and strong